Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery

Meyer, Heidi Kristina; Roberts, Emyr Martyn; Rapp, Hans Tore; Davies, Andrew J.

doi:10.1016/j.dsr.2019.103137

Cited by 55 publications

(91 citation statements)

References 67 publications

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“…Benthic-pelagic coupling mediated by selective feeding of sponges on seawater microorganisms (McMurray et al, 2016;Van Oevelen et al, 2018) in combination with the discussed hydrodynamic patterns (vertical mixing) might explain the slightly reduced microbial richness of the water body residing directly above a sponge ground (BW1 and MW1). The circumstance that sponge density and community composition changes along the topography of Schulz Bank seamount (Meyer et al, 2019;Roberts et al, 2018), can further aid to explain observed differences in microbial community composition between the other near-bed water samples (BW2-4). For these samples, we observed distinct pelagic microbial communities at a finer resolution than can be explained by the pure water masses distribution (consider depth of intermediate and deep water layers in Fig.…”

Section: A Seamount Imprint On Seawater Microbial Communitiesmentioning

confidence: 97%

“…Our results of a lower microbial richness above the seamount summit might seem contradictory at first. However, Schulz Bank is a recognized sponge ground ecosystem, with a peak in sponge density and diversity at the seamount summit (Roberts et al, 2018;Meyer et al, 2019). Sponges are very efficient suspension feeders and are known for removing large amounts of particulate organic matter including prokaryotes and small eukaryotes from the water column (Leys et al, 2018).…”

Section: A Seamount Imprint On Seawater Microbial Communitiesmentioning

confidence: 99%

“…Sponge ground ecosystems are areas harbouring high densities of structure-forming sponge individuals. The Arctic Schulz Bank seamount has been observed to host a rich and diverse community of sponges (Roberts et al, 2018;Meyer et al, 2019) and may be considered a sponge ground ecosystem harbouring a reservoir of yet unexamined microbial biodiversity.…”

Section: Introductionmentioning

confidence: 99%

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On giant shoulders: How a seamount affects the microbial community composition of seawater and sponges

Busch¹,

Hanz²,

Mienis³

et al. 2020

Preprint

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Abstract. Seamounts represent ideal systems to study the influence and interdependency of environmental gradients at a single geographic location. These topographic features represent a prominent habitat for various forms of life, including microbiota and macrobiota, spanning benthic as well as pelagic organisms. While it is known that seamounts are globally abundant structures, it still remains unclear how and to which extend the complexity of the seafloor is intertwined with the local oceanographic mosaic, biogeochemistry and microbiology of a seamount ecosystem. Along these lines, the present study aimed to explore whether and to which extend seamounts can have an imprint on the microbial community composition of seawater and of sessile benthic invertebrates, sponges. For our high-resolution sampling approach of microbial diversity (16S rRNA gene Amplicon sequencing) along with measurements of inorganic nutrients and other biogeochemical parameters, we focused on the Schulz Bank seamount ecosystem, a sponge ground ecosystem which is located on the Arctic Mid-Ocean Ridge. Seawater samples were collected at two sampling depths (mid-water: MW, and near-bed water: BW) from a total of 19 sampling sites. With a clustering approach we defined microbial micro-habitats within the pelagic realm at Schulz Bank, which were mapped onto the seamount's topography, and related to various environmental parameters (such as suspended particulate matter (SPM), dissolved inorganic carbon (DIC), silicate (SiO4−), phosphate (PO43−), ammonia (NH4+), nitrate (NO32−), nitrite (NO2

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Section: A Seamount Imprint On Seawater Microbial Communitiesmentioning

confidence: 97%

Section: A Seamount Imprint On Seawater Microbial Communitiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On giant shoulders: How a seamount affects the microbial community composition of seawater and sponges

Busch¹,

Hanz²,

Mienis³

et al. 2020

Preprint

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show abstract

“…These classifiers usually include support vector machine, random forest, neural network, etc. However, due to different shooting angles of traffic block the port, complex background and lighting, and other factors, traditional features often fail to meet the requirements, resulting in low classification accuracy [10,11].…”

Section: Design Of Image Classifiermentioning

confidence: 99%

“…We have split the total 500 samples into 400 training samples and 100 testing samples, in which the training accuracy rate reached 99.3% after 1000 iterations of the training dataset and the testing accuracy rate reached 98.2% after 10 iterations of the testing dataset. factors, traditional features often fail to meet the requirements, resulting in low classification accuracy [10,11]. Since 2012, the convolutional neural network has shown a strong advantage in image classification and its stronger feature presentation ability has also been recognized by more people [12].…”

Section: Design Of Image Classifiermentioning

confidence: 99%

Research on Image Adaptive Enhancement Algorithm under Low Light in License Plate Recognition System

Shi

Yuan

2020

Symmetry

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The traffic block port monitors and manages the road traffic by shooting and recording the motor vehicles. However, due to the complex factors such as shooting angle, light condition, environmental background, etc., the recognition rate of license plate is not high enough. High light and low light under complex lighting conditions are symmetry problems. This paper analyzes and solves the low light problem in detail, an image adaptive enhancement algorithm under low light conditions is proposed in the paper. The algorithm mainly includes four modules, among which, the fast image classification module uses the deep and separable convolutional neural network to classify low-light images into low-light images by day and low-light images by night, greatly reducing the computation burden on the basis of ensuring the classification accuracy. The image enhancement module inputs the classified images into two different image enhancement algorithms and adopts the idea of dividing and ruling; the image quality evaluation module adopts a weighted comprehensive evaluation index. The final experiment shows that the comprehensive evaluation indexes are all greater than 0.83, which can improve the subsequent recognition of vehicle face and license plate.

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Using eDNA and SCUBA surveys for detection and monitoring of a threatened marine cryptic fish

Bessell

Appleyard

Stuart‐Smith

et al. 2023

Aquatic Conservation

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Quantification of species’ spatial distributions and population trends is crucial for successful conservation efforts. Obtaining sufficient population data, however, is often difficult in the marine environment, especially for rare fish and invertebrate species that are small, cryptic and very difficult to detect. This study sought to understand the effort required to search for undiscovered populations of small, cryptic, marine species in shallow vegetated coastal habitats and track population numbers, using the Critically Endangered red handfish (Thymichthys politus) as a representative species. A sampling strategy was designed using a combination of environmental DNA (eDNA) and structured underwater scuba surveys of life‐like 3D‐printed ‘handfish replicas’ to estimate detectability and ultimately determine whether current population monitoring is adequately covering the remaining habitat occupied by the species. Tested over scales of hundreds of metres to kilometres, the eDNA assays performed relatively poorly in situ, detecting red handfish presence in only ~13% of samples collected from the centre of a known, yet low‐density, red handfish site. In contrast, underwater searches for independently placed handfish replicas by scuba divers indicated that mean detection probabilities at finer scales (~100 m) ranged from 57 to 97%. Near certain (95% probability) detection of an adult handfish was achievable with only one to three surveys (300 m2 belt transects), depending on the habitat complexity. While other species will vary in detectability using eDNA and underwater searches, these findings give insight into the general effort required for the detection of small, rare species inhabiting vegetated coastal environments. Such knowledge not only helps to refine monitoring and conservation efforts for known threatened species, but may also assist in identifying other inconspicuous species whose population declines may otherwise go unnoticed.

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Spatial patterns of arctic sponge ground fauna and demersal fish are detectable in autonomous underwater vehicle (AUV) imagery

Cited by 55 publications

References 67 publications

On giant shoulders: How a seamount affects the microbial community composition of seawater and sponges

On giant shoulders: How a seamount affects the microbial community composition of seawater and sponges

Research on Image Adaptive Enhancement Algorithm under Low Light in License Plate Recognition System

Using eDNA and SCUBA surveys for detection and monitoring of a threatened marine cryptic fish

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